07) Pedidos externos-ARTIGO.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Objetivo específico: Determinar parâmetros gerais (n° de animais nascidos, período para nascimento e sexagem) da criação animal no biotério do ICC, total e por linhagem, nos últimos 5 anos; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "#Paramentros para os gráficos\n",
    "plt.rcParams.update({'font.size': 20}) #tamanho da fonte\n",
    "plt.rcParams['xtick.labelsize'] = 18 #tamanho da fonte\n",
    "plt.rcParams['ytick.labelsize'] = 18 #tamanho da fonte\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pergunta: Dados dos requisitantes, tipos de uso - associação com linhagens e demanda e tipos de ensaios. \n",
    "Necessário ter todas essas linhagens? -  Alessandra Aguiar.\n",
    "\n",
    "Tipo de uso: Não temos informações sobre os Usuários Externos para qual tipo de uso, é realizada apenas a produção dos animais. Já os usuários internos da pra saber, porém, não pelo software BioterC"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quais são os pedidos externos e linhagens?\n",
    "Qual tipo de uso para cada linhagem?\n",
    "Qual período de pedidos para cada linhagem?\n",
    "\n",
    "Quais são os pedidos internos e as linhagens?\n",
    "Qual tipo de uso para cada linhagem?\n",
    "Qual período de pedidos para linhagem?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>solic</th>\n",
       "      <th>mail</th>\n",
       "      <th>lab</th>\n",
       "      <th>exter</th>\n",
       "      <th>ling</th>\n",
       "      <th>num_ani</th>\n",
       "      <th>time</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>caix_est</th>\n",
       "      <th>id_fim</th>\n",
       "      <th>caix_exp</th>\n",
       "      <th>data_inicio</th>\n",
       "      <th>data_solic</th>\n",
       "      <th>data_forn</th>\n",
       "      <th>data_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tania</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>x</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>2</td>\n",
       "      <td>dia</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>83050140</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>1421625600</td>\n",
       "      <td>1411391851</td>\n",
       "      <td>666</td>\n",
       "      <td>1411392413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Hálisson Tesseroli Miot</td>\n",
       "      <td>halissontm@gmail.com</td>\n",
       "      <td>LPEP</td>\n",
       "      <td>-</td>\n",
       "      <td>Swiss</td>\n",
       "      <td>4</td>\n",
       "      <td>mes</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0000000000</td>\n",
       "      <td>666</td>\n",
       "      <td>16</td>\n",
       "      <td>1-3-2-16</td>\n",
       "      <td>106</td>\n",
       "      <td>4-1-1-106</td>\n",
       "      <td>1412121600</td>\n",
       "      <td>1411583300</td>\n",
       "      <td>1412619416</td>\n",
       "      <td>1418727743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Tania</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>.</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>2</td>\n",
       "      <td>dia</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>81300</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>1420070400</td>\n",
       "      <td>1411491911</td>\n",
       "      <td>666</td>\n",
       "      <td>1411491957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Claudemir de Souza</td>\n",
       "      <td>claudemir.s@tecpar.br</td>\n",
       "      <td>VIROMOL</td>\n",
       "      <td>-</td>\n",
       "      <td>Swiss</td>\n",
       "      <td>11</td>\n",
       "      <td>dia</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>555555</td>\n",
       "      <td>666</td>\n",
       "      <td>14</td>\n",
       "      <td>1-2-7-14</td>\n",
       "      <td>113</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1412899200</td>\n",
       "      <td>1411579273</td>\n",
       "      <td>1412620096</td>\n",
       "      <td>1422037389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Camila Oliveira</td>\n",
       "      <td>halissontm@gmail.com</td>\n",
       "      <td>LPEP</td>\n",
       "      <td>-</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>6</td>\n",
       "      <td>mes</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0000000000</td>\n",
       "      <td>666</td>\n",
       "      <td>50</td>\n",
       "      <td>2-3-1-50</td>\n",
       "      <td>108</td>\n",
       "      <td>4-1-3-108</td>\n",
       "      <td>1412121600</td>\n",
       "      <td>1411583355</td>\n",
       "      <td>1412082161</td>\n",
       "      <td>1418727745</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      solic                    mail              lab exter  \\\n",
       "id                                                                           \n",
       "2                     Tania  tschepainski@gmail.com  Usuário Externo     x   \n",
       "6   Hálisson Tesseroli Miot    halissontm@gmail.com             LPEP     -   \n",
       "4                     Tania  tschepainski@gmail.com  Usuário Externo     .   \n",
       "5        Claudemir de Souza   claudemir.s@tecpar.br          VIROMOL     -   \n",
       "7           Camila Oliveira    halissontm@gmail.com             LPEP     -   \n",
       "\n",
       "      ling  num_ani time  total_time  doses         cep  cep_num_ani  id_orig  \\\n",
       "id                                                                              \n",
       "2   Balb/c        2  dia           3      2    83050140          666      666   \n",
       "6    Swiss        4  mes           2      5  0000000000          666       16   \n",
       "4   Balb/c        2  dia           2      2       81300          666      666   \n",
       "5    Swiss       11  dia          30      5      555555          666       14   \n",
       "7   Balb/c        6  mes           2      5  0000000000          666       50   \n",
       "\n",
       "    caix_est  id_fim   caix_exp  data_inicio  data_solic   data_forn  \\\n",
       "id                                                                     \n",
       "2        AAA     666        AAA   1421625600  1411391851         666   \n",
       "6   1-3-2-16     106  4-1-1-106   1412121600  1411583300  1412619416   \n",
       "4        AAA     666        AAA   1420070400  1411491911         666   \n",
       "5   1-2-7-14     113        NaN   1412899200  1411579273  1412620096   \n",
       "7   2-3-1-50     108  4-1-3-108   1412121600  1411583355  1412082161   \n",
       "\n",
       "      data_fim  \n",
       "id              \n",
       "2   1411392413  \n",
       "6   1418727743  \n",
       "4   1411491957  \n",
       "5   1422037389  \n",
       "7   1418727745  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lendo tabela referente a pedidos\n",
    "ped = pd.read_csv('../../tabelas_test/pedido_2019-06-18.csv', index_col='id')\n",
    "ped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4168"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Numero total de pedidos de usuários externos\n",
    "ped[ped['lab'] == 'Usuário Externo']['num_ani'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1608"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Numero total de pedidos internos\n",
    "ped[ped['lab'] != 'Usuário Externo']['num_ani'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mesmo não havendo muitos pedidos pro grupo de Swiss, é a segunda linhagem mais pedida em comparação as outras, seguida do Balb/c."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Balb/c       215\n",
       "Swiss         82\n",
       "C57BL/6       37\n",
       "S129KO        21\n",
       "C57BL06WT     15\n",
       "Swiss-2        9\n",
       "S129WT         6\n",
       "Swiss-1        3\n",
       "C3H            2\n",
       "AG129          2\n",
       "DBA/1J         1\n",
       "Name: ling, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pedido de todos os labs externos e internos\n",
    "ped['ling'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "      <th>data_inicio</th>\n",
       "      <th>data_solic</th>\n",
       "      <th>data_forn</th>\n",
       "      <th>data_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AG129</th>\n",
       "      <td>34</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>228</td>\n",
       "      <td>1332</td>\n",
       "      <td>1332</td>\n",
       "      <td>3073183200</td>\n",
       "      <td>3072654732</td>\n",
       "      <td>1332</td>\n",
       "      <td>3076982883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Balb/c</th>\n",
       "      <td>2368</td>\n",
       "      <td>2281</td>\n",
       "      <td>772</td>\n",
       "      <td>111102</td>\n",
       "      <td>132739456122</td>\n",
       "      <td>93973738465</td>\n",
       "      <td>320543108767</td>\n",
       "      <td>320728904351</td>\n",
       "      <td>258132858896</td>\n",
       "      <td>299677883430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3H</th>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>1332</td>\n",
       "      <td>4294967294</td>\n",
       "      <td>4294967294</td>\n",
       "      <td>2995765200</td>\n",
       "      <td>2995507986</td>\n",
       "      <td>2995938565</td>\n",
       "      <td>2995938565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C57BL/6</th>\n",
       "      <td>1310</td>\n",
       "      <td>577</td>\n",
       "      <td>69</td>\n",
       "      <td>23474</td>\n",
       "      <td>62277029816</td>\n",
       "      <td>55846189976</td>\n",
       "      <td>56908162800</td>\n",
       "      <td>56728274438</td>\n",
       "      <td>49045750862</td>\n",
       "      <td>56763934276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C57BL06WT</th>\n",
       "      <td>535</td>\n",
       "      <td>232</td>\n",
       "      <td>13</td>\n",
       "      <td>9990</td>\n",
       "      <td>19327354483</td>\n",
       "      <td>19327354459</td>\n",
       "      <td>21807982800</td>\n",
       "      <td>21788893554</td>\n",
       "      <td>20357519393</td>\n",
       "      <td>21813660180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBA/1J</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>490</td>\n",
       "      <td>1950101194</td>\n",
       "      <td>11010112</td>\n",
       "      <td>1556766000</td>\n",
       "      <td>1556809204</td>\n",
       "      <td>1556809299</td>\n",
       "      <td>1558552428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129KO</th>\n",
       "      <td>287</td>\n",
       "      <td>62</td>\n",
       "      <td>13</td>\n",
       "      <td>11281</td>\n",
       "      <td>22680575229</td>\n",
       "      <td>12120249147</td>\n",
       "      <td>31177602000</td>\n",
       "      <td>31172811116</td>\n",
       "      <td>31190229719</td>\n",
       "      <td>31203070063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129WT</th>\n",
       "      <td>88</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>3996</td>\n",
       "      <td>6442451258</td>\n",
       "      <td>6442451230</td>\n",
       "      <td>8737362000</td>\n",
       "      <td>8737017456</td>\n",
       "      <td>8740465714</td>\n",
       "      <td>8740465714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swiss</th>\n",
       "      <td>933</td>\n",
       "      <td>852</td>\n",
       "      <td>218</td>\n",
       "      <td>58003</td>\n",
       "      <td>64202025883</td>\n",
       "      <td>55368104630</td>\n",
       "      <td>121226025600</td>\n",
       "      <td>121188286723</td>\n",
       "      <td>104867027109</td>\n",
       "      <td>121505411645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swiss-1</th>\n",
       "      <td>74</td>\n",
       "      <td>41</td>\n",
       "      <td>3</td>\n",
       "      <td>846</td>\n",
       "      <td>4328977427</td>\n",
       "      <td>4294967655</td>\n",
       "      <td>4545968400</td>\n",
       "      <td>4543782157</td>\n",
       "      <td>4546782270</td>\n",
       "      <td>4549905933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swiss-2</th>\n",
       "      <td>43</td>\n",
       "      <td>89</td>\n",
       "      <td>37</td>\n",
       "      <td>900</td>\n",
       "      <td>2218505376</td>\n",
       "      <td>3924</td>\n",
       "      <td>13705203600</td>\n",
       "      <td>13702338696</td>\n",
       "      <td>10642051105</td>\n",
       "      <td>13741743708</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           num_ani  total_time  doses  cep_num_ani       id_orig       id_fim  \\\n",
       "ling                                                                            \n",
       "AG129           34          42      2          228          1332         1332   \n",
       "Balb/c        2368        2281    772       111102  132739456122  93973738465   \n",
       "C3H             14          31      2         1332    4294967294   4294967294   \n",
       "C57BL/6       1310         577     69        23474   62277029816  55846189976   \n",
       "C57BL06WT      535         232     13         9990   19327354483  19327354459   \n",
       "DBA/1J          10           1      1          490    1950101194     11010112   \n",
       "S129KO         287          62     13        11281   22680575229  12120249147   \n",
       "S129WT          88          23      2         3996    6442451258   6442451230   \n",
       "Swiss          933         852    218        58003   64202025883  55368104630   \n",
       "Swiss-1         74          41      3          846    4328977427   4294967655   \n",
       "Swiss-2         43          89     37          900    2218505376         3924   \n",
       "\n",
       "            data_inicio    data_solic     data_forn      data_fim  \n",
       "ling                                                               \n",
       "AG129        3073183200    3072654732          1332    3076982883  \n",
       "Balb/c     320543108767  320728904351  258132858896  299677883430  \n",
       "C3H          2995765200    2995507986    2995938565    2995938565  \n",
       "C57BL/6     56908162800   56728274438   49045750862   56763934276  \n",
       "C57BL06WT   21807982800   21788893554   20357519393   21813660180  \n",
       "DBA/1J       1556766000    1556809204    1556809299    1558552428  \n",
       "S129KO      31177602000   31172811116   31190229719   31203070063  \n",
       "S129WT       8737362000    8737017456    8740465714    8740465714  \n",
       "Swiss      121226025600  121188286723  104867027109  121505411645  \n",
       "Swiss-1      4545968400    4543782157    4546782270    4549905933  \n",
       "Swiss-2     13705203600   13702338696   10642051105   13741743708  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "soma_todos = ped.groupby('ling')\n",
    "soma_lings = soma_todos.sum()\n",
    "soma_lings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "COMEÇA AQUI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eloiza/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>solic</th>\n",
       "      <th>mail</th>\n",
       "      <th>lab</th>\n",
       "      <th>exter</th>\n",
       "      <th>ling</th>\n",
       "      <th>num_ani</th>\n",
       "      <th>time</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>caix_est</th>\n",
       "      <th>id_fim</th>\n",
       "      <th>caix_exp</th>\n",
       "      <th>data_inicio</th>\n",
       "      <th>data_solic</th>\n",
       "      <th>data_forn</th>\n",
       "      <th>data_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tania</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>x</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>2</td>\n",
       "      <td>dia</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>83050140</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>2015-01-19</td>\n",
       "      <td>2014-09-22 13:17:31</td>\n",
       "      <td>1970-01-01 00:11:06</td>\n",
       "      <td>2014-09-22 13:26:53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Tania</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>.</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>2</td>\n",
       "      <td>dia</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>81300</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>666</td>\n",
       "      <td>AAA</td>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>2014-09-23 17:05:11</td>\n",
       "      <td>1970-01-01 00:11:06</td>\n",
       "      <td>2014-09-23 17:05:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Phileno</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>UEL</td>\n",
       "      <td>Swiss</td>\n",
       "      <td>25</td>\n",
       "      <td>mes</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3433</td>\n",
       "      <td>666</td>\n",
       "      <td>20</td>\n",
       "      <td>1-3-6-20</td>\n",
       "      <td>1</td>\n",
       "      <td>1-1-1-1</td>\n",
       "      <td>2014-10-07</td>\n",
       "      <td>2014-09-29 13:33:14</td>\n",
       "      <td>2014-10-01 17:33:31</td>\n",
       "      <td>2014-10-01 17:33:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Phileno</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>UEL</td>\n",
       "      <td>Balb/c</td>\n",
       "      <td>120</td>\n",
       "      <td>dia</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>00000</td>\n",
       "      <td>666</td>\n",
       "      <td>54</td>\n",
       "      <td>2-3-5-54</td>\n",
       "      <td>1</td>\n",
       "      <td>1-1-1-1</td>\n",
       "      <td>2014-12-01</td>\n",
       "      <td>2014-09-29 19:27:01</td>\n",
       "      <td>2014-10-01 17:51:45</td>\n",
       "      <td>2014-10-01 17:51:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Phileno</td>\n",
       "      <td>tschepainski@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>UEL</td>\n",
       "      <td>C57BL06WT</td>\n",
       "      <td>120</td>\n",
       "      <td>dia</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>000000</td>\n",
       "      <td>666</td>\n",
       "      <td>96</td>\n",
       "      <td>3-4-5-96</td>\n",
       "      <td>1</td>\n",
       "      <td>1-1-1-1</td>\n",
       "      <td>2014-10-08</td>\n",
       "      <td>2014-10-01 18:14:28</td>\n",
       "      <td>2014-10-01 18:37:50</td>\n",
       "      <td>2014-10-01 18:37:50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       solic                    mail              lab exter       ling  \\\n",
       "id                                                                       \n",
       "2      Tania  tschepainski@gmail.com  Usuário Externo     x     Balb/c   \n",
       "4      Tania  tschepainski@gmail.com  Usuário Externo     .     Balb/c   \n",
       "9   Phileno   tschepainski@gmail.com  Usuário Externo   UEL      Swiss   \n",
       "10   Phileno  tschepainski@gmail.com  Usuário Externo   UEL     Balb/c   \n",
       "12   Phileno  tschepainski@gmail.com  Usuário Externo   UEL  C57BL06WT   \n",
       "\n",
       "    num_ani time  total_time  doses       cep  cep_num_ani  id_orig  caix_est  \\\n",
       "id                                                                              \n",
       "2         2  dia           3      2  83050140          666      666       AAA   \n",
       "4         2  dia           2      2     81300          666      666       AAA   \n",
       "9        25  mes           2      3      3433          666       20  1-3-6-20   \n",
       "10      120  dia          40     12     00000          666       54  2-3-5-54   \n",
       "12      120  dia          12      2    000000          666       96  3-4-5-96   \n",
       "\n",
       "    id_fim caix_exp data_inicio          data_solic           data_forn  \\\n",
       "id                                                                        \n",
       "2      666      AAA  2015-01-19 2014-09-22 13:17:31 1970-01-01 00:11:06   \n",
       "4      666      AAA  2015-01-01 2014-09-23 17:05:11 1970-01-01 00:11:06   \n",
       "9        1  1-1-1-1  2014-10-07 2014-09-29 13:33:14 2014-10-01 17:33:31   \n",
       "10       1  1-1-1-1  2014-12-01 2014-09-29 19:27:01 2014-10-01 17:51:45   \n",
       "12       1  1-1-1-1  2014-10-08 2014-10-01 18:14:28 2014-10-01 18:37:50   \n",
       "\n",
       "              data_fim  \n",
       "id                      \n",
       "2  2014-09-22 13:26:53  \n",
       "4  2014-09-23 17:05:57  \n",
       "9  2014-10-01 17:33:31  \n",
       "10 2014-10-01 17:51:45  \n",
       "12 2014-10-01 18:37:50  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Criando uma variável para receber o filtro só de usuários externos\n",
    "pedidos_ext = ped[(ped['lab'] == 'Usuário Externo') & \n",
    "                  (ped['num_ani'] < 200) & \n",
    "                  (ped['exter'] != 'Teste') &\n",
    "                  (ped['exter'] != 'Teste BioterC') &\n",
    "                  (ped['exter'] != 'Institute Nagib Lab')] \n",
    "\n",
    "#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "#Transformando todas as datas\n",
    "\n",
    "datas = ['data_inicio', 'data_solic', 'data_forn', 'data_fim']\n",
    "\n",
    "for d in datas:\n",
    "    pedidos_ext[d] = pd.to_datetime(pedidos_ext[d], unit = 's') #indica o formato das datas\n",
    "    \n",
    "pedidos_ext.head()\n",
    "#pedidos_ext[pedidos_ext['exter'] == 'C3H']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pedidos_ext)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #verificando pedidos externos para relatório do Giovanny\n",
    "# pedidos_ext[(pedidos_ext['mail'] == 'bordignonjuliano@gmail.com') & (pedidos_ext['ling']=='S129KO')]['num_ani'].sum()\n",
    "                                                             \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Verificando a soma dos animais dessa linhagem:\n",
    "#ped[ped['ling'] == 'C57BL06WT']['num_ani'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Verificando a soma dos animais dessa linhagem:\n",
    "#ped[ped['ling'] == 'C57BL/6']['num_ani'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eloiza/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py:5890: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._update_inplace(new_data)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BALB/c     78\n",
       "C57BL/6    48\n",
       "Swiss      32\n",
       "S129KO     14\n",
       "S129WT      6\n",
       "C3H         2\n",
       "Name: ling, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Substituindo linhagem 'C57BL06WT' por 'C57BL/6' - \"concatenando as linhagens\"\n",
    "pedidos_ext['ling'].replace('C57BL06WT', 'C57BL/6', inplace=True)\n",
    "\n",
    "pedidos_ext['ling'].replace('Balb/c', 'BALB/c', inplace=True)\n",
    "\n",
    "pedidos_ext['ling'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Após \"concatenação\" foi somado o valor da linhagem C57BL/6 (porem, não esta dando o valor correto da soma) \n",
    "# pedidos_ext[pedidos_ext['ling'] == 'C3H']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BALB/c     78\n",
       "C57BL/6    48\n",
       "Swiss      32\n",
       "S129KO     14\n",
       "S129WT      6\n",
       "C3H         2\n",
       "Name: ling, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Substituindo linhagem 'Swiss-1', 'Swiss-2' por 'Swiss' - \"concatenando as linhagens\"\n",
    "pedidos_ext['ling'].replace(['Swiss-1', 'Swiss-2'],'Swiss' ,inplace=True)\n",
    "pedidos_ext['ling'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "682"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Ao somar a linhagem Swiss era para retornar um valor maior\n",
    "pedidos_ext[pedidos_ext['ling'] == 'Swiss']['num_ani'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BALB/c</th>\n",
       "      <td>1392</td>\n",
       "      <td>906</td>\n",
       "      <td>160</td>\n",
       "      <td>51948</td>\n",
       "      <td>64190850032</td>\n",
       "      <td>60467856096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3H</th>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>1332</td>\n",
       "      <td>4294967294</td>\n",
       "      <td>4294967294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C57BL/6</th>\n",
       "      <td>1780</td>\n",
       "      <td>739</td>\n",
       "      <td>63</td>\n",
       "      <td>31226</td>\n",
       "      <td>79456899249</td>\n",
       "      <td>75173542597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129KO</th>\n",
       "      <td>85</td>\n",
       "      <td>36</td>\n",
       "      <td>6</td>\n",
       "      <td>9324</td>\n",
       "      <td>11942755795</td>\n",
       "      <td>9922754927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129WT</th>\n",
       "      <td>88</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>3996</td>\n",
       "      <td>6442451258</td>\n",
       "      <td>6442451230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swiss</th>\n",
       "      <td>682</td>\n",
       "      <td>374</td>\n",
       "      <td>42</td>\n",
       "      <td>21312</td>\n",
       "      <td>45003787282</td>\n",
       "      <td>36689966697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         num_ani  total_time  doses  cep_num_ani      id_orig       id_fim\n",
       "ling                                                                      \n",
       "BALB/c      1392         906    160        51948  64190850032  60467856096\n",
       "C3H           14          31      2         1332   4294967294   4294967294\n",
       "C57BL/6     1780         739     63        31226  79456899249  75173542597\n",
       "S129KO        85          36      6         9324  11942755795   9922754927\n",
       "S129WT        88          23      2         3996   6442451258   6442451230\n",
       "Swiss        682         374     42        21312  45003787282  36689966697"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = pedidos_ext.groupby('ling')\n",
    "g.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UFPR                                                  40\n",
       "UEL                                                   12\n",
       "UFPR - Departamento de Fisiologia                     12\n",
       "Universidade Federal do Paraná                         8\n",
       "Laboratorio de Virologia Molecular - ICC - Fiocruz     8\n",
       "Viromol                                                7\n",
       "UFSC                                                   5\n",
       "Universidade Federal do Rio de Janeiro                 5\n",
       "Pontifícia Universidade Católica do Paraná             5\n",
       "Universidade Estadual de Londrina-UEL                  5\n",
       "UNIVALI                                                4\n",
       "Viromol ICC                                            4\n",
       "Universidade Estadual de Londrina                      4\n",
       "Universidade Federal de Santa Catarina                 3\n",
       "Biotério                                               3\n",
       "ViroMol                                                3\n",
       "IBMP                                                   3\n",
       "ICC                                                    2\n",
       "Universidade de São Paulo                              2\n",
       "UFPR - Biologia Celular                                2\n",
       "LabGen                                                 2\n",
       "Vriromol                                               1\n",
       "REG                                                    1\n",
       "BIOVET                                                 1\n",
       "ICC - teste                                            1\n",
       "Name: exter, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pedidos_ext['exter'].value_counts()[:25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UFPR                                            68\n",
       "ICC                                             40\n",
       "UEL                                             21\n",
       "UFSC                                             8\n",
       "EXTERNO                                          8\n",
       "UFRJ                                             6\n",
       "Biotério                                         5\n",
       "Pontifícia Universidade Católica do Paraná       5\n",
       "UNIVALI                                          5\n",
       "Universidade Federal da Fronteira Sul            4\n",
       "IBMP                                             4\n",
       "UFSM                                             2\n",
       "Universidade de São Paulo                        2\n",
       "Immunova                                         1\n",
       "FIOCRUZ - Centro de Pesquisa Aggeu Magalhães     1\n",
       "BIOVET                                           1\n",
       "Universidade Estadual do Oeste do Paraná         1\n",
       "Fiocruz Bahia                                    1\n",
       "Name: exter, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pedidos_ext['exter'].replace(('Universidade Federal do Paraná','UNiversidade Federal do Parana', 'Ufpr', 'ufpr','UfPR',\n",
    "                             'UFPR - Biologia Celular', 'UFPR - Departamento de Fisiologia', 'UFPR - LABMICRO','UFPR - Centro Politécnico'), 'UFPR', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace(('Universidade Estadual de Londrina-UEL','Universidade Estadual de Londrina'), 'UEL', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace(('Viromol','ViroMol','Vriromol','Lab viromol', 'Virologia', 'Virologia Molecular Fiocruz',\n",
    "                             'Laboratorio de Virologia Molecular - ICC - Fiocruz', 'Virologia '), 'Viromol ICC', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace((' Universidade da Fronteira sul','Universidade da Fronteira sul',\n",
    "                              'UNiversidade Federal da Fronteira Sul'), 'Universidade Federal da Fronteira Sul', inplace=True)\n",
    "#pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace('Univali', 'UNIVALI', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace('Universidade Federal de Santa Catarina', 'UFSC', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace('Universidade Federal do Rio de Janeiro', 'UFRJ', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace('Instituto de Biologia Molecular do Paraná', 'IBMP', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace(('Instituto Carlos Chagas','ICC - teste', 'LabGen', 'LPEP', 'LABCET', 'Labreg', 'REG', 'Genomica',\n",
    "                             'Lab Reg', 'GEN', 'BiomolTrip', 'Viromol ICC'), 'ICC', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace('Universidade Federal de Santa Maria - UFSM', 'UFSM', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace(('biotério','BIOT TESTE'), 'Biotério', inplace=True)\n",
    "# pedidos_ext['exter'].value_counts()\n",
    "#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "pedidos_ext['exter'].replace(('Test exter','externo','x','.','Lab Test','wded','Externo'), 'EXTERNO', inplace=True)\n",
    "pedidos_ext['exter'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>solic</th>\n",
       "      <th>mail</th>\n",
       "      <th>lab</th>\n",
       "      <th>exter</th>\n",
       "      <th>ling</th>\n",
       "      <th>num_ani</th>\n",
       "      <th>time</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>caix_est</th>\n",
       "      <th>id_fim</th>\n",
       "      <th>caix_exp</th>\n",
       "      <th>data_inicio</th>\n",
       "      <th>data_solic</th>\n",
       "      <th>data_forn</th>\n",
       "      <th>data_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Giovanny mazzarotto</td>\n",
       "      <td>mazzarotto@tecpar.br</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>Biotério</td>\n",
       "      <td>S129WT</td>\n",
       "      <td>18</td>\n",
       "      <td>dia</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>LW-XX/XX</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>5-1-8-148&lt;br /&gt;5-1-6-146&lt;</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>1-1-6-6&lt;br /&gt;1-1-6-6&lt;br /</td>\n",
       "      <td>2014-11-11 05:00:00</td>\n",
       "      <td>2014-11-11 16:55:32</td>\n",
       "      <td>2014-11-11 17:07:56</td>\n",
       "      <td>2014-11-11 17:07:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Giovanny mazzarotto</td>\n",
       "      <td>mazzarotto@tecpar.br</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>Biotério</td>\n",
       "      <td>S129KO</td>\n",
       "      <td>18</td>\n",
       "      <td>dia</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>LW-XX/XX</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>5-4-7-171&lt;br /&gt;5-4-6-170&lt;</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>1-1-6-6&lt;br /&gt;1-1-6-6&lt;br /</td>\n",
       "      <td>2014-11-11 05:00:00</td>\n",
       "      <td>2014-11-11 17:02:26</td>\n",
       "      <td>2014-11-11 17:12:23</td>\n",
       "      <td>2014-11-11 17:12:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>Teste 1</td>\n",
       "      <td>pereira.liviah@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>Biotério</td>\n",
       "      <td>BALB/c</td>\n",
       "      <td>5</td>\n",
       "      <td>dia</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>LW-15/13</td>\n",
       "      <td>666</td>\n",
       "      <td>385</td>\n",
       "      <td>8-1</td>\n",
       "      <td>386</td>\n",
       "      <td>8-2</td>\n",
       "      <td>2017-04-17 03:00:00</td>\n",
       "      <td>2017-04-12 13:25:27</td>\n",
       "      <td>2017-04-12 14:04:46</td>\n",
       "      <td>2017-04-12 14:04:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>Tania</td>\n",
       "      <td>tania.schepainski@fiocruz.br</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>Biotério</td>\n",
       "      <td>BALB/c</td>\n",
       "      <td>1</td>\n",
       "      <td>dia</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>LW-15/13</td>\n",
       "      <td>666</td>\n",
       "      <td>385</td>\n",
       "      <td>8-1</td>\n",
       "      <td>386</td>\n",
       "      <td>8-2</td>\n",
       "      <td>2017-04-12 03:00:00</td>\n",
       "      <td>2017-04-12 14:00:28</td>\n",
       "      <td>2017-04-12 14:03:10</td>\n",
       "      <td>2017-04-12 14:03:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>Lívia H. G. Pereira</td>\n",
       "      <td>pereira.liviah@gmail.com</td>\n",
       "      <td>Usuário Externo</td>\n",
       "      <td>Biotério</td>\n",
       "      <td>Swiss</td>\n",
       "      <td>8</td>\n",
       "      <td>mes</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>LW-15/13</td>\n",
       "      <td>666</td>\n",
       "      <td>44010125</td>\n",
       "      <td>1-44&lt;br /&gt;1-25</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>7-45&lt;br /&gt;7-37</td>\n",
       "      <td>2017-05-09 03:00:00</td>\n",
       "      <td>2017-05-08 19:20:08</td>\n",
       "      <td>2017-05-09 12:56:21</td>\n",
       "      <td>2017-05-09 12:56:21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   solic                          mail              lab  \\\n",
       "id                                                                        \n",
       "19   Giovanny mazzarotto          mazzarotto@tecpar.br  Usuário Externo   \n",
       "20   Giovanny mazzarotto          mazzarotto@tecpar.br  Usuário Externo   \n",
       "202              Teste 1      pereira.liviah@gmail.com  Usuário Externo   \n",
       "203                Tania  tania.schepainski@fiocruz.br  Usuário Externo   \n",
       "205  Lívia H. G. Pereira      pereira.liviah@gmail.com  Usuário Externo   \n",
       "\n",
       "        exter    ling  num_ani time  total_time  doses       cep  cep_num_ani  \\\n",
       "id                                                                              \n",
       "19   Biotério  S129WT       18  dia          21      1  LW-XX/XX          666   \n",
       "20   Biotério  S129KO       18  dia          21      1  LW-XX/XX          666   \n",
       "202  Biotério  BALB/c        5  dia           1      1  LW-15/13          666   \n",
       "203  Biotério  BALB/c        1  dia           2      1  LW-15/13          666   \n",
       "205  Biotério   Swiss        8  mes           2      4  LW-15/13          666   \n",
       "\n",
       "        id_orig                   caix_est      id_fim  \\\n",
       "id                                                       \n",
       "19   2147483647  5-1-8-148<br />5-1-6-146<  2147483647   \n",
       "20   2147483647  5-4-7-171<br />5-4-6-170<  2147483647   \n",
       "202         385                        8-1         386   \n",
       "203         385                        8-1         386   \n",
       "205    44010125             1-44<br />1-25  2147483647   \n",
       "\n",
       "                      caix_exp         data_inicio          data_solic  \\\n",
       "id                                                                       \n",
       "19   1-1-6-6<br />1-1-6-6<br / 2014-11-11 05:00:00 2014-11-11 16:55:32   \n",
       "20   1-1-6-6<br />1-1-6-6<br / 2014-11-11 05:00:00 2014-11-11 17:02:26   \n",
       "202                        8-2 2017-04-17 03:00:00 2017-04-12 13:25:27   \n",
       "203                        8-2 2017-04-12 03:00:00 2017-04-12 14:00:28   \n",
       "205             7-45<br />7-37 2017-05-09 03:00:00 2017-05-08 19:20:08   \n",
       "\n",
       "              data_forn            data_fim  \n",
       "id                                           \n",
       "19  2014-11-11 17:07:56 2014-11-11 17:07:56  \n",
       "20  2014-11-11 17:12:23 2014-11-11 17:12:23  \n",
       "202 2017-04-12 14:04:46 2017-04-12 14:04:46  \n",
       "203 2017-04-12 14:03:10 2017-04-12 14:03:10  \n",
       "205 2017-05-09 12:56:21 2017-05-09 12:56:21  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pedidos_ext[pedidos_ext['exter'] == 'Biotério']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.figure(figsize=(15,10))\n",
    "# plt.title('Solicitações Usuários Externos')\n",
    "\n",
    "# plot = pedidos_ext.groupby('exter')\n",
    "# plot['num_ani'].sum().sort_values(ascending=True).plot(\n",
    "# kind='barh'\n",
    "# )\n",
    "# plt.xlabel('Número de Animais') #definindo nome do eixo X\n",
    "# plt.ylabel('Laboratórios') #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/instituicoes_ext_I.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>exter</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BIOVET</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>666</td>\n",
       "      <td>45</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Biotério</th>\n",
       "      <td>50</td>\n",
       "      <td>47</td>\n",
       "      <td>8</td>\n",
       "      <td>3330</td>\n",
       "      <td>4338978189</td>\n",
       "      <td>6442451713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXTERNO</th>\n",
       "      <td>20</td>\n",
       "      <td>53</td>\n",
       "      <td>13</td>\n",
       "      <td>5328</td>\n",
       "      <td>2147487097</td>\n",
       "      <td>2147487651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIOCRUZ - Centro de Pesquisa Aggeu Magalhães</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>2147483647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fiocruz Bahia</th>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>2147483647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBMP</th>\n",
       "      <td>264</td>\n",
       "      <td>51</td>\n",
       "      <td>3</td>\n",
       "      <td>1922</td>\n",
       "      <td>4294967803</td>\n",
       "      <td>4294967561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICC</th>\n",
       "      <td>167</td>\n",
       "      <td>599</td>\n",
       "      <td>66</td>\n",
       "      <td>26640</td>\n",
       "      <td>29268658646</td>\n",
       "      <td>24156518663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Immunova</th>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>2147483647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pontifícia Universidade Católica do Paraná</th>\n",
       "      <td>80</td>\n",
       "      <td>15</td>\n",
       "      <td>8</td>\n",
       "      <td>3330</td>\n",
       "      <td>3562213845</td>\n",
       "      <td>24713483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UEL</th>\n",
       "      <td>1195</td>\n",
       "      <td>322</td>\n",
       "      <td>30</td>\n",
       "      <td>13986</td>\n",
       "      <td>34359739854</td>\n",
       "      <td>34359739687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UFPR</th>\n",
       "      <td>1647</td>\n",
       "      <td>945</td>\n",
       "      <td>115</td>\n",
       "      <td>45288</td>\n",
       "      <td>94743957077</td>\n",
       "      <td>85998198868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UFRJ</th>\n",
       "      <td>115</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>3996</td>\n",
       "      <td>10737418399</td>\n",
       "      <td>8600944700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UFSC</th>\n",
       "      <td>29</td>\n",
       "      <td>68</td>\n",
       "      <td>15</td>\n",
       "      <td>5328</td>\n",
       "      <td>4337978156</td>\n",
       "      <td>5425069222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UFSM</th>\n",
       "      <td>78</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1332</td>\n",
       "      <td>4294967294</td>\n",
       "      <td>4294967294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNIVALI</th>\n",
       "      <td>164</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>3330</td>\n",
       "      <td>8589935254</td>\n",
       "      <td>8589935254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Universidade Estadual do Oeste do Paraná</th>\n",
       "      <td>36</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "      <td>666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Universidade Federal da Fronteira Sul</th>\n",
       "      <td>208</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2664</td>\n",
       "      <td>8589934588</td>\n",
       "      <td>6509461102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Universidade de São Paulo</th>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>1332</td>\n",
       "      <td>517</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              num_ani  total_time  doses  \\\n",
       "exter                                                                      \n",
       "BIOVET                                              3           3      5   \n",
       "Biotério                                           50          47      8   \n",
       "EXTERNO                                            20          53     13   \n",
       "FIOCRUZ - Centro de Pesquisa Aggeu Magalhães       10           1      1   \n",
       "Fiocruz Bahia                                      20           1      1   \n",
       "IBMP                                              264          51      3   \n",
       "ICC                                               167         599     66   \n",
       "Immunova                                           27           1      1   \n",
       "Pontifícia Universidade Católica do Paraná         80          15      8   \n",
       "UEL                                              1195         322     30   \n",
       "UFPR                                             1647         945    115   \n",
       "UFRJ                                              115           6      6   \n",
       "UFSC                                               29          68     15   \n",
       "UFSM                                               78           2      2   \n",
       "UNIVALI                                           164           5      8   \n",
       "Universidade Estadual do Oeste do Paraná           36          15      1   \n",
       "Universidade Federal da Fronteira Sul             208           4      4   \n",
       "Universidade de São Paulo                           8           4     10   \n",
       "\n",
       "                                              cep_num_ani      id_orig  \\\n",
       "exter                                                                    \n",
       "BIOVET                                                666           45   \n",
       "Biotério                                             3330   4338978189   \n",
       "EXTERNO                                              5328   2147487097   \n",
       "FIOCRUZ - Centro de Pesquisa Aggeu Magalhães          666   2147483647   \n",
       "Fiocruz Bahia                                         666   2147483647   \n",
       "IBMP                                                 1922   4294967803   \n",
       "ICC                                                 26640  29268658646   \n",
       "Immunova                                              666   2147483647   \n",
       "Pontifícia Universidade Católica do Paraná           3330   3562213845   \n",
       "UEL                                                 13986  34359739854   \n",
       "UFPR                                                45288  94743957077   \n",
       "UFRJ                                                 3996  10737418399   \n",
       "UFSC                                                 5328   4337978156   \n",
       "UFSM                                                 1332   4294967294   \n",
       "UNIVALI                                              3330   8589935254   \n",
       "Universidade Estadual do Oeste do Paraná              666          666   \n",
       "Universidade Federal da Fronteira Sul                2664   8589934588   \n",
       "Universidade de São Paulo                            1332          517   \n",
       "\n",
       "                                                   id_fim  \n",
       "exter                                                      \n",
       "BIOVET                                                110  \n",
       "Biotério                                       6442451713  \n",
       "EXTERNO                                        2147487651  \n",
       "FIOCRUZ - Centro de Pesquisa Aggeu Magalhães   2147483647  \n",
       "Fiocruz Bahia                                  2147483647  \n",
       "IBMP                                           4294967561  \n",
       "ICC                                           24156518663  \n",
       "Immunova                                       2147483647  \n",
       "Pontifícia Universidade Católica do Paraná       24713483  \n",
       "UEL                                           34359739687  \n",
       "UFPR                                          85998198868  \n",
       "UFRJ                                           8600944700  \n",
       "UFSC                                           5425069222  \n",
       "UFSM                                           4294967294  \n",
       "UNIVALI                                        8589935254  \n",
       "Universidade Estadual do Oeste do Paraná              666  \n",
       "Universidade Federal da Fronteira Sul          6509461102  \n",
       "Universidade de São Paulo                             234  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testando = pedidos_ext.groupby('exter')\n",
    "testando.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_INST = pedidos_ext[pedidos_ext['exter'] == 'FIOCRUZ - Centro de Pesquisa Aggeu Magalhães']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>S129KO</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>666</td>\n",
       "      <td>2147483647</td>\n",
       "      <td>2147483647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        num_ani  total_time  doses  cep_num_ani     id_orig      id_fim\n",
       "ling                                                                   \n",
       "S129KO       10           1      1          666  2147483647  2147483647"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_de_novo = test_INST.groupby('ling')\n",
    "test_de_novo.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.figure(figsize=(15,10))\n",
    "# plt.title('Mediana do período de acasalamento ao nascimento por linhagem')\n",
    "\n",
    "# plot = pedidos_ext.groupby('exter')\n",
    "# plot['num_ani'].sum().sort_values(ascending=True).plot(\n",
    "# kind='barh'\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BALB/c</th>\n",
       "      <td>1392</td>\n",
       "      <td>906</td>\n",
       "      <td>160</td>\n",
       "      <td>51948</td>\n",
       "      <td>64190850032</td>\n",
       "      <td>60467856096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C57BL/6</th>\n",
       "      <td>1780</td>\n",
       "      <td>739</td>\n",
       "      <td>63</td>\n",
       "      <td>31226</td>\n",
       "      <td>79456899249</td>\n",
       "      <td>75173542597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swiss</th>\n",
       "      <td>682</td>\n",
       "      <td>374</td>\n",
       "      <td>42</td>\n",
       "      <td>21312</td>\n",
       "      <td>45003787282</td>\n",
       "      <td>36689966697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         num_ani  total_time  doses  cep_num_ani      id_orig       id_fim\n",
       "ling                                                                      \n",
       "BALB/c      1392         906    160        51948  64190850032  60467856096\n",
       "C57BL/6     1780         739     63        31226  79456899249  75173542597\n",
       "Swiss        682         374     42        21312  45003787282  36689966697"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ling_mais_soli_ano = ['BALB/c','C57BL/6','Swiss']\n",
    "\n",
    "g_ling_mais_ped_ex = pedidos_ext[pedidos_ext['ling'].isin(ling_mais_soli_ano)].groupby('ling')\n",
    "lin_mais_ped_ex = g_ling_mais_ped_ex.sum()\n",
    "lin_mais_ped_ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ling</th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C57BL/6</td>\n",
       "      <td>1780</td>\n",
       "      <td>739</td>\n",
       "      <td>63</td>\n",
       "      <td>31226</td>\n",
       "      <td>79456899249</td>\n",
       "      <td>75173542597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BALB/c</td>\n",
       "      <td>1392</td>\n",
       "      <td>906</td>\n",
       "      <td>160</td>\n",
       "      <td>51948</td>\n",
       "      <td>64190850032</td>\n",
       "      <td>60467856096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Swiss</td>\n",
       "      <td>682</td>\n",
       "      <td>374</td>\n",
       "      <td>42</td>\n",
       "      <td>21312</td>\n",
       "      <td>45003787282</td>\n",
       "      <td>36689966697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ling  num_ani  total_time  doses  cep_num_ani      id_orig       id_fim\n",
       "0  C57BL/6     1780         739     63        31226  79456899249  75173542597\n",
       "1   BALB/c     1392         906    160        51948  64190850032  60467856096\n",
       "2    Swiss      682         374     42        21312  45003787282  36689966697"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns_plot_ped_ex = lin_mais_ped_ex.groupby('ling').sum().sort_values(by='num_ani',ascending=False).reset_index()\n",
    "sns_plot_ped_ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "# plt.title('Strains with more External Requests')\n",
    "\n",
    "sns.barplot(x='ling',\n",
    "    y='num_ani', palette=\"GnBu_d\",\n",
    "    data=sns_plot_ped_ex).set_xticklabels(\n",
    "                            rotation=45,\n",
    "                            horizontalalignment='right',\n",
    "    labels=sns_plot_ped_ex['ling']\n",
    ")\n",
    "\n",
    "#plt.legend([str(plot_media) + ' mean mouse/strain', str(plot_mediana) + ' median mouse/strain'])\n",
    "plt.xlabel('Mouse strain') #definindo nome do eixo X\n",
    "plt.ylabel('Number of mice') #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "plt.savefig(\n",
    "    fname=\"../../resultados/numero_ped_ext_fig6-ARTIGO.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "    bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "    dpi=300, #numero de pixels da imagem?\n",
    "    transparent=True #deixar o gráfico transparente\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.06372933487120339, 0.06372933487120339, 0.06372933487120339),\n",
       " (0.12745866974240677, 0.12745866974240677, 0.12745866974240677),\n",
       " (0.2011534025374856, 0.2011534025374856, 0.2011534025374856),\n",
       " (0.2786620530565167, 0.2786620530565167, 0.2786620530565167),\n",
       " (0.35100346020761247, 0.35100346020761247, 0.35100346020761247),\n",
       " (0.40784313725490196, 0.40784313725490196, 0.40784313725490196),\n",
       " (0.4655132641291811, 0.4655132641291811, 0.4655132641291811),\n",
       " (0.5257977700884275, 0.5257977700884275, 0.5257977700884275),\n",
       " (0.5906343713956171, 0.5906343713956171, 0.5906343713956171),\n",
       " (0.6578085351787775, 0.6578085351787775, 0.6578085351787775),\n",
       " (0.7249826989619378, 0.7249826989619378, 0.7249826989619378),\n",
       " (0.7777777777777778, 0.7777777777777778, 0.7777777777777778),\n",
       " (0.826005382545175, 0.826005382545175, 0.826005382545175),\n",
       " (0.8729104190695886, 0.8729104190695886, 0.8729104190695886),\n",
       " (0.9125259515570934, 0.9125259515570934, 0.9125259515570934),\n",
       " (0.9483275663206459, 0.9483275663206459, 0.9483275663206459),\n",
       " (0.9741637831603229, 0.9741637831603229, 0.9741637831603229)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_pallet = sns.color_palette('Greys_r',17)\n",
    "test_pallet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "# plt.title('Strains with more External Requests')\n",
    "\n",
    "sns.barplot(x='ling',\n",
    "    y='num_ani', palette=test_pallet,\n",
    "    data=sns_plot_ped_ex).set_xticklabels(\n",
    "                            rotation=45,\n",
    "                            horizontalalignment='right',\n",
    "    labels=sns_plot_ped_ex['ling']\n",
    ")\n",
    "\n",
    "#plt.legend([str(plot_media) + ' mean mouse/strain', str(plot_mediana) + ' median mouse/strain'])\n",
    "plt.xlabel('Mouse strain') #definindo nome do eixo X\n",
    "plt.ylabel('Number of mice') #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "plt.savefig(\n",
    "    fname=\"../../resultados/numero_ped_ext_fig6-ILAR.JPEG\", #pasta e nome do arquivo onde vai ser salvo\n",
    "    bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "    dpi=300, #numero de pixels da imagem?\n",
    "    transparent=True #deixar o gráfico transparente\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.figure(figsize=(10,5))\n",
    "# plt.title('Strains with more External Requests',**csfont)\n",
    "\n",
    "# plot = lin_mais_ped_ex.groupby('ling')\n",
    "# plot['num_ani'].sum().sort_values(ascending=True).plot(\n",
    "# kind='barh'\n",
    "\n",
    "# )\n",
    "# plt.xlabel('Number of mice', **csfont) #definindo nome do eixo X\n",
    "# plt.ylabel('Mouse Strain',**csfont) #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/animais_mais_ext_fig6a-ARTIGO.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=300, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_ani</th>\n",
       "      <th>total_time</th>\n",
       "      <th>doses</th>\n",
       "      <th>cep_num_ani</th>\n",
       "      <th>id_orig</th>\n",
       "      <th>id_fim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C3H</th>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>1332</td>\n",
       "      <td>4294967294</td>\n",
       "      <td>4294967294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129KO</th>\n",
       "      <td>85</td>\n",
       "      <td>36</td>\n",
       "      <td>6</td>\n",
       "      <td>9324</td>\n",
       "      <td>11942755795</td>\n",
       "      <td>9922754927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S129WT</th>\n",
       "      <td>88</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>3996</td>\n",
       "      <td>6442451258</td>\n",
       "      <td>6442451230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        num_ani  total_time  doses  cep_num_ani      id_orig      id_fim\n",
       "ling                                                                    \n",
       "C3H          14          31      2         1332   4294967294  4294967294\n",
       "S129KO       85          36      6         9324  11942755795  9922754927\n",
       "S129WT       88          23      2         3996   6442451258  6442451230"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ling_menos_soli_ano = ['S129KO', 'S129WT', 'C3H' ]\n",
    "\n",
    "g_ling_menos_ped_ex = pedidos_ext[pedidos_ext['ling'].isin(ling_menos_soli_ano)].groupby('ling')\n",
    "lin_menos_ped_ex = g_ling_menos_ped_ex.sum()\n",
    "lin_menos_ped_ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.figure(figsize=(10,5))\n",
    "# plt.title('Linhagens com menos Solicitações Externas')\n",
    "\n",
    "# plot = lin_menos_ped_ex.groupby('ling')\n",
    "# plot['num_ani'].sum().sort_values(ascending=True).plot(\n",
    "# kind='barh'\n",
    "\n",
    "# )\n",
    "# plt.xlabel('Número de Animais') #definindo nome do eixo X\n",
    "# plt.ylabel('Linhagens') #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/animais_menos_ext_I.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SÉRIES TEMPORAIS + MODELO PREDITIVO PARA PEDIDOS EXTERNOS "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ling</th>\n",
       "      <th>exter</th>\n",
       "      <th>num_ani</th>\n",
       "      <th>data_forn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>data_solic</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-09-22 13:17:31</th>\n",
       "      <td>Balb/c</td>\n",
       "      <td>EXTERNO</td>\n",
       "      <td>2</td>\n",
       "      <td>1970-01-01 00:11:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-23 17:05:11</th>\n",
       "      <td>Balb/c</td>\n",
       "      <td>EXTERNO</td>\n",
       "      <td>2</td>\n",
       "      <td>1970-01-01 00:11:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-29 13:33:14</th>\n",
       "      <td>Swiss</td>\n",
       "      <td>UEL</td>\n",
       "      <td>25</td>\n",
       "      <td>2014-10-01 17:33:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-29 19:27:01</th>\n",
       "      <td>Balb/c</td>\n",
       "      <td>UEL</td>\n",
       "      <td>120</td>\n",
       "      <td>2014-10-01 17:51:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-10-01 18:14:28</th>\n",
       "      <td>C57BL/6</td>\n",
       "      <td>UEL</td>\n",
       "      <td>120</td>\n",
       "      <td>2014-10-01 18:37:50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        ling    exter  num_ani           data_forn\n",
       "data_solic                                                        \n",
       "2014-09-22 13:17:31   Balb/c  EXTERNO        2 1970-01-01 00:11:06\n",
       "2014-09-23 17:05:11   Balb/c  EXTERNO        2 1970-01-01 00:11:06\n",
       "2014-09-29 13:33:14    Swiss      UEL       25 2014-10-01 17:33:31\n",
       "2014-09-29 19:27:01   Balb/c      UEL      120 2014-10-01 17:51:45\n",
       "2014-10-01 18:14:28  C57BL/6      UEL      120 2014-10-01 18:37:50"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Determinar o período de data de pedido e data de fornecimento\n",
    "pedido_df = pd.DataFrame(pedidos_ext['data_solic'])\n",
    "pedido_df['ling'] = pedidos_ext['ling']\n",
    "pedido_df['exter'] = pedidos_ext['exter']\n",
    "pedido_df['num_ani'] = pedidos_ext['num_ani']\n",
    "pedido_df['data_forn'] = pedidos_ext['data_forn']\n",
    "pedido_df = pedido_df.set_index('data_solic')\n",
    "pedido_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Gráfico de série temporal por linhagem somando os meses \n",
    "# serie_ling = pedido_df[pedido_df['exter']=='UEL'].resample('M').sum() #pedidos externos somando os meses\n",
    "# decom = seasonal_decompose(serie_ling, freq=12)\n",
    "\n",
    "# # Plotagem de gráfico ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# plt.figure(figsize=(25, 15))\n",
    "# plt.title('Decomposição da Série Temporal Nascimento de Animais') \n",
    "# plt.legend(['Decomposição da Série Temporal Nascimento de Animais'])\n",
    "\n",
    "# plt.subplot(4, 1, 1)\n",
    "# plt.plot(serie_ling, label = 'Nº solicitações Swiss', color='red')\n",
    "# plt.legend(loc = 'best')\n",
    "# plt.title('Decomposição da Série Temporal: Pedidos Externos - somando os meses em 5 anos') \n",
    "\n",
    "# plt.subplot(4, 1, 2)\n",
    "# plt.plot(decom.trend, label = 'Tendência', color='green')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.subplot(4, 1, 3)\n",
    "# plt.plot(decom.seasonal, label = 'Sazonalidade', color='blue')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.subplot(4, 1, 4)\n",
    "# plt.plot(decom.resid, label = 'Aleatoriedade', color='grey')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.xlabel('Data Nascimento')\n",
    "# plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Gráfico de série temporal por linhagem somando os meses \n",
    "# serie_ling = pedido_df.resample('W').sum()\n",
    "# decom = seasonal_decompose(serie_ling, freq=12)\n",
    "\n",
    "# # Plotagem de gráfico ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# plt.figure(figsize=(25, 15))\n",
    "# plt.title('Decomposição da Série Temporal Nascimento de Animais') \n",
    "# plt.legend(['Decomposição da Série Temporal Nascimento de Animais'])\n",
    "\n",
    "# plt.subplot(4, 1, 1)\n",
    "# plt.plot(serie_ling, label = 'Nº solicitações Swiss', color='red')\n",
    "# plt.legend(loc = 'best')\n",
    "# plt.title('Decomposição da Série Temporal: Pedidos Externos - somando as semanas em 5 anos') \n",
    "\n",
    "# plt.subplot(4, 1, 2)\n",
    "# plt.plot(decom.trend, label = 'Tendência', color='green')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.subplot(4, 1, 3)\n",
    "# plt.plot(decom.seasonal, label = 'Sazonalidade', color='blue')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.subplot(4, 1, 4)\n",
    "# plt.plot(decom.resid, label = 'Aleatoriedade', color='grey')\n",
    "# plt.legend(loc = 'best')\n",
    "\n",
    "# plt.xlabel('Data Nascimento')\n",
    "# plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from statsmodels.tsa.arima_model import ARIMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# previsao = pedido_df.resample('M').sum()               #somando mês a mês\n",
    "# previsao = previsao['num_ani']                                     #para trabalhar com a previsão deve usar uma série, na qual foi escolhida 'num_ani'\n",
    "# previsao.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pedido_df.index.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for p in range(3):                                    #laço com tamanho 3 para p\n",
    "#     for q in range(3):                                #laço com tamanho 3 para q\n",
    "#         for d in range(3):                            #laço com tamanho 3 para d\n",
    "#             test = (p, q, d)                          #guardando p,q,d em uma variável\n",
    "#             modelo = ARIMA(previsao, order=test, freq='M')  #modelo ARIMA\n",
    "#             try:                                      #tente\n",
    "#                 results = modelo.fit()                #usando a função fit\n",
    "#                 print(f'({p}, {q}, {d})')             #printando os valores ajustados\n",
    "#                 print(results.summary())              #resumo dos parâmetros\n",
    "#                 print()\n",
    "#             except: \n",
    "#                 print('Não')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# teste = ARIMA(previsao, order=(1, 1, 1))                  # dentro de order temos (p, q, d) p n° de termos auto regressivos, q n° da média móvel (muveing average), d n° de diferenças ñ sazonais\n",
    "# modelo_tr = teste.fit()                             #ajusta o modelo ARIMA (p, d, q)\n",
    "# modelo_tr.summary() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #AJUUUUUSTAR os parametros\n",
    "\n",
    "# #previsão somando todas as linhagens mês a mês\n",
    "\n",
    "# prev = modelo_tr.forecast(steps=12)                                            #que irá te retornar a previsão para o período definido, que pode ser dias, meses, anos,\n",
    "# plt.figure(figsize=(25, 5))\n",
    "# modelo_tr.plot_predict('2018-06', '2020-06',                                   #decedindo o período de previsão\n",
    "#                        ax = previsao.plot(),\n",
    "#                        plot_insample=True\n",
    "#                       )\n",
    "# plt.rcParams.update({'font.size': 20}) #tamanho da fonte\n",
    "# plt.title('Ajuste Modelo ARIMA(1,1,1) Previsão para dois anos - Pedidos Externos')\n",
    "\n",
    "# plt.xlabel('Períodos') #definindo nome do eixo X\n",
    "# plt.ylabel('Número de Animais') #definindo nome do eixo Y\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando os gráficos\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/previsao_sol_ext.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gráfico solicitação de animais usuários externos linhagens mais pedidas ano a ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "inic = pedidos_ext.loc[pedidos_ext.index.min(), 'data_solic'] #loc: localizador - localizando a primeira data\n",
    "fim = pedidos_ext.loc[pedidos_ext.index.max(), 'data_solic']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ling_mais_soli_ano = ['Balb/c','C57BL/6','Swiss']\n",
    "\n",
    "# plt.figure(figsize=(15, 5))\n",
    "# for l in ling_mais_soli_ano:\n",
    "#     pedido_df[pedido_df['ling'] == l]['num_ani'].resample('A').sum().plot()\n",
    "\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Editando o gráfico\n",
    "\n",
    "# plt.title(f'Linhagens mais solicitadas Usuário Externo por ano {inic.day}/{inic.month}/{inic.year} até {fim.day}/{fim.month}/{fim.year}')\n",
    "# plt.legend(ling_mais_soli_ano)\n",
    "# plt.xlabel('Solicitações externas durante os 5 anos')\n",
    "# plt.ylabel('Soma de animais')\n",
    "# #++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando o gráfico\n",
    "\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/solic_usuarioexterno_mais_ano_I.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gráfico solicitação de animais usuários externos linhagens mais pedidas mês a mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ling_mais_soli_mes = ['Balb/c', 'C57BL/6','Swiss']\n",
    "\n",
    "# plt.figure(figsize=(15, 5))\n",
    "# for c in ling_mais_soli_mes:\n",
    "#     pedido_df[pedido_df['ling'] == c]['num_ani'].groupby([lambda x: x.month]).sum().plot()\n",
    "\n",
    "# #++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Editando o gráfico\n",
    "# plt.title(f'Linhagens mais solicitadas Usuários Externos por mês {inic.day}/{inic.month}/{inic.year} até {fim.day}/{fim.month}/{fim.year}')\n",
    "# plt.legend(ling_mais_soli_mes)\n",
    "# plt.xlabel('Mês Nascimento')\n",
    "# plt.ylabel('Soma de animais')\n",
    "\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# # #Salvando o gráfico\n",
    "\n",
    "# # plt.savefig(\n",
    "# #     fname=\"../resultados/13_pergunta_solic_usuarioexterno_mais_mes.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "# #     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "# #     dpi=150, #numero de pixels da imagem?\n",
    "# #     transparent=True #deixar o gráfico transparente\n",
    "# # )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gráfico solicitação de animais usuários externos linhagens menos pedidas ano a ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ling_menos_soli_ano = ['S129KO', 'S129WT', 'C3H' ]\n",
    "\n",
    "# plt.figure(figsize=(15, 5))\n",
    "# for l in ling_menos_soli_ano:\n",
    "#     pedido_df[pedido_df['ling'] == l]['num_ani'].resample('A').sum().plot()\n",
    "    \n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Editando o gráfico\n",
    "\n",
    "# plt.title(f'Linhagens menos solicitadas Usuário Externo por ano {inic.day}/{inic.month}/{inic.year} até {fim.day}/{fim.month}/{fim.year}')\n",
    "# plt.legend(ling_menos_soli_ano)\n",
    "# plt.xlabel('Solicitações externas durante os 5 anos')\n",
    "# plt.ylabel('Soma de animais')\n",
    "\n",
    "# # #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando o gráfico\n",
    "# plt.savefig(\n",
    "#     fname=\"../../resultados/solic_usuarioexterno_menos_ano.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gráfico solicitação de animais usuários externos linhagens menos pedidas mês a mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ling_menos_soli_mes = ['S129KO', 'S129WT', 'C3H' ]\n",
    "\n",
    "# plt.figure(figsize=(15, 5))\n",
    "# for c in ling_menos_soli_mes:\n",
    "#     pedido_df[pedido_df['ling'] == c]['num_ani'].groupby([lambda x: x.month]).sum().plot()\n",
    "\n",
    "# #++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Editando o gráfico\n",
    "\n",
    "# plt.title(f'Linhagens menos solicitadas Usuários Externos por mês {inic.day}/{inic.month}/{inic.year} até {fim.day}/{fim.month}/{fim.year}')\n",
    "# plt.legend(ling_menos_soli_mes)\n",
    "# plt.xlabel('Mês Nascimento')\n",
    "# plt.ylabel('Soma de animais')\n",
    "\n",
    "# #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n",
    "# #Salvando o gráfico\n",
    "\n",
    "# plt.savefig(\n",
    "#     fname=\"../resultados/13_pergunta_solic_usuarioexterno_menos_mes.png\", #pasta e nome do arquivo onde vai ser salvo\n",
    "#     bbox_inches='tight', #função que deixa o gráfico mais próxima da margem\n",
    "#     dpi=150, #numero de pixels da imagem?\n",
    "#     transparent=True #deixar o gráfico transparente\n",
    "# )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Primeiros Resultados: As solicitações de Usuários externos é quase 3 vezes maior que internas, com um total de 4168 solicitações no período de 5 anos. Nas solicitações de animais como um todo, a linhagem com mais evento é a Balb/c (isogênica), em seguida a linhagem Swiss (heterogênica e em terceiro lugar a linhagem C57BL/6. Ao filtrar os dados apenas para pedidos externos, a linhagem mais solicitada é o C57BL/6, em segundo lugar a linhagem Balb/c e em terceiro a linhagem Swiss.\n",
    "\n",
    "Resultado por período anual (linhagens mais pedidas):\n",
    "C57BL/6 - Solicitação desde 2014 se manteve constante entre os anos de 2015 a 2017, sendo sua produção superior nos anos de 2018 e 2019.\n",
    "\n",
    "Balb/c - teve um pico maior de solicitação em 2015 e 2018 e teve uma menor produção no ano de 2016 e 2017.\n",
    "\n",
    "Swiss - Entre 2015, 2016 e 2019 foi o menor período de solicitação e maior produção entre 2017 e 2018.\n",
    "\n",
    "Resultado por períodos mensal(linhagens mais pedidas):\n",
    "C57BL/6 - Solicitação constante entre todos os mêses, exceto mês de Maio que demonstra menor solicitação.\n",
    "\n",
    "Balb/c - Menor solicitação entre os mêses de Abril, Julho e Agosto.\n",
    "\n",
    "Swiss - Solicitação baixa em comparação as outras linhagens e Menor solicitação entre os mêses de Abril até Junho.\n",
    "\n",
    "Resultado por período anual (linhagens menos pedidas):\n",
    "S129 WT - Sem solicitações no ano de 2015, sendo solicitada no ano de 2016 e baixa em 2017 - Não há registros de solicitações pra 2018 e 2019.\n",
    "\n",
    "S129KO - Com solicitação no ano de 2015 e 2017 sem solicitação em 2016. - Não há registros de solicitações pra 2018 e 2019.\n",
    "\n",
    "C3H - Apenas uma solicitação externa de 4 camundongos 2019(confirmar) (não apresentado no gráfico).\n",
    "\n",
    "Resultado por período mensal (linhagens menos pedidas):\n",
    "S129 WT - Sem solicitação entre os mêses de Janeiro a Abril, com maior solicitação de Junho a Outubro.\n",
    "\n",
    "S129 KO - Maior solicitação entre Outubro e Dezembro, nos demais meses se manteve constante.\n",
    "\n",
    "C3H - Sem solicitações."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}